Simultaneous Quantification of Multiple rRNA Targets in Complex Target Samples

Microarray-based approaches identify microorganisms by hybridizing target genes (i.e., rRNA or rRNA genes) to oligonucleotide probes. The drawbacks of these approaches are: (i) probe design methods generate probes whose behavior correlate poorly to signal intensity; (ii) stringent washing conditions remove specific targets rather than nonspecific ones; and (iii) nonspecific target binding (cross-hybridization) hampers accurate identification of specific targets in complex target mixtures. An approach circumventing these drawbacks is highly desired.

Objectives: (i) to quantify specific targets at varying concentrations using a novel microarray approach, (ii) to ascertain if prescreening of probes based on selectivity measurements improve target quantification, and (iii) to determine the detection limits for quantifying specific targets in mixtures containing both known and unknown targets.

Methods: Signals from an array of probes that completely or partially match the target sequence were considered as a hybridization fingerprint of that target. Quantities of each microbe in a sample were calculated by deconvoluting the hybridization pattern using a library of target fingerprints. The library of fingerprints was built by recording the fingerprints of rRNA from 10 microbial targets. The quality of the approach was assessed by the R2 of the regression line of actual and estimated (i) probe signal intensities and (ii) target concentrations.

Results: A good agreement between actual and estimated quantities was found for 24 model mixtures consisting of 7, 8, and 10 targets at different concentrations. Prescreening of the probes using a selectivity measure (i.e., maximum signal intensity divided by sum of all intensities for a probe), drastically improved the quality of the quantifications, making quantifications possible. Accurate quantification of targets was possible in the range of 0.01 to 1.0 nM in mixtures.

Conclusion: This novel microarray approach allows simultaneous identification and quantification of multiple oral microorganisms and may be useful for the analysis of polymicrobial communities.